A goal of (bio-)process analytics, above all, in the context of the PAT guideline of the FDA (US Food and Drug Administration), is lastly improving productivity while obtaining constant quality in the face of trying to shorten product introduction time. The acronym PAT stands for “Process Analytical Technology”. The PAT guideline was created by the FDA as a stimulus and aid for optimizing, analysis and control of pharmaceutical manufacturing processes. The critical process parameters of a biopharmaceutical manufacturing process influencing the critical quality properties are to be analyzed and controlled corresponding to this guideline. The critical process parameters (per the PAT guideline, CPP for short) are control variables of the process, which enter into the corresponding control algorithms for process control. In the following, these parameters are also referred to as control parameters. To be distinguished therefrom are the parameters relevant to product quality (referred to in the PAT guideline as critical quality attributes, or CQA for short). These parameters serve as measures for product quality, but are not currently used as control parameters for the production process. The control parameters influence parameters relevant to product quality.
An example of the importance of bioprocess control is provided by the production of recombinant proteins. The heterologous gene expression is induced only after reaching a certain cell density. Within the two-phase cultivation process, consequently, both the cell growth as well as also the change to the metabolic phase, in which the product formation takes place, must be exactly monitored and controlled. Between cell growth and product production, which cannot be process dependently directly correlated with one another, a robust, reproducible process method/-regime must be determined by optimizing the cultivation conditions.
As explained, for example, in Rodrigues, M. E., Costa, A. R., Henriques, M. Azeredo, J., Oliveira, R. (2010). Technological progresses in monoclonal antibody production systems. Biotechnol Prog, 26 (2), Pgs. 332-351, an approach is the optimizing of the nutrient supply. In this regard, nutrients, especially metabolism educts, above all glucose, glutamine, and metabolism products, such as e.g. lactate, ammonium, glutamate, thus generally the metabolites, are to be reliably determined (Rodrigues et al., Pg. 343, left, 4th paragraph). The term, metabolite, means here and in the following not only a product or intermediate product of metabolism, but, instead, generally, a material participating in the metabolism, especially metabolism educts, intermediate products of metabolism and products of metabolism. Too low, however, also too high, metabolite concentrations (increased formation of toxic products) can lead to reduction of cell growth and/or productivity. Direct monitoring of the formed product would be extremely valuable and important for cell line selection and optimizing the cultivation parameters (Rodrigues et al. Pg. 343, right, 4th paragraph). A system, which within one and the same process-connected automation platform can exactly determine a number of critical process parameters, on the one hand, from the group of the metabolites and, on the other hand, from the group of the specific products, would be even more helpful.
The concept underpinning the PAT guideline aims to control the process by defining suitable control parameters, which are registered online, and thereby to achieve a desired product quality in a more efficient manner. Essential for the control of bioprocesses in the sense of the PAT-guideline is, consequently, the presence, respectively the development, of suitable online-enabled, sensor technology; i.e. sensors and process connected, analytical measurements technology.
Classic control parameters, especially also for the control of bioprocesses, include most often chemical/physical state variables, such as e.g. temperature, pH-value, CO2, O2 content, whose determination is established or at least possible by means of inline sensor technology. With biosensor-based measuring systems, other control parameters can be determined, which would not be accessible with classic, established measurements technology. Due to the instability of biological components, such systems have not proved themselves sufficient for routine inline use, so that for biosensor-based measuring systems the taking of a sample and delivery of such to a measuring cell is necessary. Biosensor determined control parameters include, for example, metabolites, thus nutrients or products of metabolism, whose content curve during a biological process has direct influence on the process control, in order to tune to optimal conditions for product manufacture—with the required quality.
The determining of product quality parameters, the CQAs, delivers direct information, whether the product has the required properties within an established tolerance range, especially a tolerance range defined by the relevant authorities for pharmaceutical production. Currently for determining the CQAs, samples taken daily manually from the process are examined in the laboratory following a lapse of time and, in such case, a multiplicity of product quality parameters are determined with corresponding laboratory analysis devices. Most often, only after process end are all samples examined together. The testing of the samples requires trained personnel for carrying out the involved tasks and for interpreting the results. A reaction to/handling of failure to achieve the desired product characteristics is not possible in the case of such a procedure.
Already known from the state of the art are some methods for determining individual CQAs and CPPs as well as commercially available analytical devices for performing these methods. These are set forth in the following Table I. In order that such devices can be applied in an automated manner in process measurements technology for monitoring, respectively for control of, production processes, a process connection is required, via which they can be connected with the process, in order to perform measurements, respectively remove samples from the process for the measurements. Table I indicates whether the respective analytical devices utilize a process connection.
TABLE ICQA:ProzessCQA: productproductMethodDeviceconnectionamountqualityCPP: metaboliteHPLCe.g. UltiMate 3000 HPLCnoyesyesnoSystems (ThermoScientificDionex, ThermoFisher Scientific Inc.,Waltham, MA, US)ELISAMost often, manualnoyesyesnoAmperometric,YSI Flownamics SEG-yes (fornonoyesenzyme sensorsFlOWlaboratory-(YSI Inc./Xylem Inc.,reactor)Yellow Springs, Ohio, US)Bioprofile-Analyzer (NovanononoyesBiomedical Corporation,Waltham, MA, US)Biosensor-Arrays (JobstnononoyesTechnologies GmbH,Freiburg, DE)BioPAT Trace (SartoriusyesnonoyesStedim Biotech GmbH,(laboratory)Goettingen, DE)PhotometricKonelab (Thermo Fishernoyes (onlynoyesScientific, Inc., Waltham,Immunoglobuline)MA, US), CuBiAn andCedex Bio (F. Hoffmann-La Roche AG, Basel, CH)Separate labBaychromat Process/Labyes (laboratoryyes (only fornoyesdevices united(Bayer Technologyand process)Immunoglobulineunder a control unitServices GmbH,asLeverkusen, DE)product)
Known from German Patent, EP 1698891 A1 is a method for reducing the measurement deviation of amperometric biosensors. This document concerns modifying the operation with potentials when an electrical mediator is applied as transmitting mediator of the actual redox reaction of the analyte. The systematic error of the so-called background current, above all, at the beginning of the reaction after storage and before application, is said to be reduced by the claimed procedure.
Described in German Patent, DE 3406223 A1 and U.S. Pat. No. 3,655,958 is an analytical device for automatically performing the standard addition method, wherein the US patent refers to spectral photometers.
Described in US Published Patent Application 2007/0224702 A1 is a method for determining a plurality of analytes in one or more samples, wherein each analyte is detected with its own affinity assay.
German Patent, DE 196 12 766 A1 describes a method for analysis of a complex biological system, in the case of which metabolism parameters are ascertained by means of ligand receptor interaction based on samples taken from a fermenter. Control of the process occurs via sensors arranged in the fermenter.
Known from German Patent, DE 10 2010 064 391 A1 is a method and an analytical device for automated determining of an analyte content of a liquid sample. This basically also permits detection of a number of different analytes in samples from a process liquid supplied one after the other to a measuring cell.
Described in Published Patent Application US 2005/0208473 A1 is a method for control of a bioprocess, in the case of which different control parameters are registered by sensors arranged in the bioreactor, among others, enzyme electrodes.
Known from Published Patent Application US 2007/0292958 A1 is an apparatus, in the case of which process liquid is removed from a fermentation process via a micro-dialysis probe and can be fed to an analytical apparatus for determining metabolite concentrations.
Described in Published Patent Application US 2008/0241966 A1 are a method and an apparatus, which are suitable for automated determining of various metabolites in a liquid sample.